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9 March 2022 Photonic TPU ASIC for AI acceleration
Volker J. Sorger
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Proceedings Volume PC12019, AI and Optical Data Sciences III; PC120190J (2022) https://doi.org/10.1117/12.2613809
Event: SPIE OPTO, 2022, San Francisco, California, United States
Abstract
With Moore’s law and Dennard scaling now being limited by fundamental physics, the trend in processor heterogeneity suggests the possibility for special-purpose photonic processors such as neural networks or RF-signal & image filtering. Here unique opportunities exist, for example, given by algorithmic parallelism of analog and distributed non-van Neuman architectures enabling non-iterative O(1) processors with ps-short delay towards real-time decision making. Here, I will share our latest work on photonic information processors to include a photonic tensor core including multistate photonic nonvolatile random-access memory [Appl. Phys. Rev.], and a massively parallel Fourier-optics convolutional processor [Optica]. In summary, photonics connects the worlds of electronics and optics, thus enabling new concepts of efficient intelligence information processing via algorithm-hardware homomorphism empowered by the distinctive properties of light.
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Volker J. Sorger "Photonic TPU ASIC for AI acceleration", Proc. SPIE PC12019, AI and Optical Data Sciences III, PC120190J (9 March 2022); https://doi.org/10.1117/12.2613809
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KEYWORDS
Artificial intelligence
Image processing
Data processing
Image filtering
Neural networks
Parallel computing
Physics
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